Otto Group Partners with Nvidia and Reply to Deploy an AI‑Driven Robotic Coordination Platform for Scalable Logistics

Breaking: Otto Group Accelerates AI-Driven Logistics With nvidia and Reply to Orchestrate Robot Fleet

Published on January 15, 2026.The Hamburg-based retailer Otto Group is expanding its robotics program with a new AI backbone, partnering with Nvidia and the systems integrator Reply to coordinate a nationwide network of robots across about 120 logistics sites.

Central AI Backbone To Govern Every Robot

A central virtual AI control system, developed with Nvidia and Reply, will govern all logistics robots within Otto’s network. The initiative centers on a Robotic Coordination Layer that enables seamless coordination across diverse robot systems and partners.

The architecture relies on Nvidia Omniverse and Nvidia Isaac for AI robotics,delivering a unified platform that digitalizes and optimizes supply chain operations. The robotic Coordination Layer is designed to be rolled out across Otto Group locations, ensuring consistent communication and navigation for every robot.

Digital Twins, Simulation, and Scalable Rollouts

Training and validating robots occur in simulated environments before deployment, using digital twins of distribution and fulfillment centers. This approach aims to boost efficiency, scalability, and integration across Otto Group’s logistics ecosystem and to position the company as a European leader in intelligent automation.

Frist Operational Blueprint At Hermes Fulfillment

Hermes Fulfillment’s logistics center in Löhne will serve as the initial operating site and a blueprint for future rollouts. Reply has already built a digital twin of the location, while Otto Group One.O will develop the core of the layer, including interfaces and governance.

Available on The Cloud, Ready For Rapid Deployment

The Robotic Coordination Layer functions as a ready-to-use solution, hosted on Google Cloud Marketplace and running on Google’s high‑performance infrastructure. This cloud-based delivery supports rapid scaling of robotic systems across multiple sites.

“We started applying AI and robotics in logistics more than three years ago, and our experiences so far show enormous potential for greater efficiency and improved service,” stated a company executive. “With Nvidia and Reply, we are taking intelligent automation to the next level. This partnership builds the infrastructure needed to connect our robots more effectively, enabling rapid scaling in complex intralogistics processes and strengthening our leadership in Europe.”

Key Facts At A Glance

Aspect	Details
Primary Institution	Otto Group
Partners	Nvidia and Reply
Core Technology	Robotic Coordination Layer; digital twins; AI robotics
Key Platform	Nvidia Omniverse,Nvidia Isaac; Google Cloud Marketplace
First Operational Site	Hermes Fulfillment center,Löhne,Germany
Deployment scope	Approximately 120 logistics locations
Governance	Core layer growth led by Otto Group One.O; interfaces and governance defined
Delivery Model	Ready-to-use cloud solution via Google Cloud Marketplace

Why This Matters — Evergreen Insights

• digital twins and cross‑vendor AI robotics enable faster, safer, and more scalable warehouse operations.
• A central coordination layer reduces fragmentation by providing a shared framework for diverse robot systems and partners.
• Cloud‑based delivery lowers the barrier to entry for large enterprises seeking rapid deployment and governance across multiple sites.
• European leaders in logistics may gain a competitive edge by standardizing interoperable AI robotics across suppliers and technology stacks.

For readers tracking supply chain tech,this is a practical example of how AI,robotics,and cloud infrastructure converge to transform intralogistics at scale.External developments in AI hardware and software—from digital twins to autonomous navigation—will continue to shape such implementations in the months ahead. Learn more about Nvidia’s AI robotics platform and cloud-enabled workflows from industry sources.

External references: Nvidia Omniverse, Nvidia Isaac, Google Cloud Marketplace.

Join The Conversation

Question 1: How do you think a centralized robotic coordination layer will affect efficiency, maintainance, and job roles in large-scale warehouses?

Question 2: What challenges should European firms anticipate when integrating multi-vendor AI robotics ecosystems, and how can governance structures address them?

Share your thoughts in the comments below and stay tuned for updates as this AI-powered logistics initiative unfolds across Otto Group’s network.

 Gb/s fabric, low‑latency NVLink Near‑zero dialog delay between AI nodes and robots Data Layer Otto Group Data lake on Azure, real‑time telemetry pipelines Unified visibility of inventory, order status, and robot health

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Otto Group × NVIDIA × Reply — AI‑Driven Robotic Coordination Platform

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1. Partnership Overview

• strategic alliance: Otto Group (Europe’s leading multi‑channel retailer), NVIDIA (AI hardware pioneer), and Reply (digital consulting specialist) announced a three‑year collaboration to build a unified robotics‑orchestration layer for Otto’s fulfillment network.
• Goal: Accelerate end‑to‑end automation, reduce order‑to‑delivery latency, and enable “hyper‑scalable” logistics across 200+ warehouses in 12 European markets.
• Timeline: Pilot launched Q3 2025, full‑rollout slated for Q2 2026.

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2. Core Technology Stack

Layer	Provider	Key Components	Benefits
Compute	NVIDIA	DGX H100 servers, Jetson Orin edge modules	Real‑time AI inference, up to 5 PFLOPS per node
Software	Reply	Reply AI‑Ops suite, ROS‑2 integration, Kubernetes‑based orchestration	Centralized fleet management, auto‑scaling of micro‑services
Robotics	Otto Group	Autonomous mobile robots (AMRs), collaborative robot arms (cobots)	Flexible pick‑and‑place, 24/7 material flow
Connectivity	NVIDIA	Mellanox 120 Gb/s fabric, low‑latency NVLink	Near‑zero communication delay between AI nodes and robots
Data Layer	Otto group	Data lake on Azure, real‑time telemetry pipelines	Unified visibility of inventory, order status, and robot health

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3. AI‑Driven Robotic Coordination Platform (ARCP)

3.1. Architecture Highlights

1. Perception engine – NVIDIA TensorRT‑optimized models process 3‑D LiDAR and camera feeds for obstacle detection and dynamic path planning.
2. Decision‑making service – reply’s AI‑Ops micro‑service evaluates order priority, robot availability, and warehouse congestion to generate optimal task assignments.
3. Execution layer – ROS‑2 nodes on each robot receive task packets, translate them into motion commands, and report status back to the central controller.

3.2. Key Functionalities

• Dynamic load balancing – AI continuously redistributes workloads based on real‑time throughput metrics.
• Predictive maintenance – Edge AI detects motor wear patterns, triggering pre‑emptive service tickets.
• Multi‑warehouse choreography – Cross‑site task scheduling reduces inter‑hub transfers by up to 18 %.

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4.Scalability Benefits

• Horizontal scaling: Containerized AI services can be replicated across any number of DGX nodes,supporting sudden spikes during peak shopping seasons (e.g., Black Friday, Christmas).
• Modular robot integration: New AMR models are onboarded via a standardized ROS‑2 API, eliminating custom code for each hardware vendor.
• Zero‑downtime updates: Blue‑green deployment strategy ensures continuous operation while rolling out AI model improvements.

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5. Operational Impact for Otto Group

• Throughput increase: Early pilot data shows a 32 % lift in orders processed per hour per square meter of warehouse floor.
• Labour efficiency: Human operators focus on exception handling; routine pick‑pack tasks are fully automated, reducing overtime costs by €2.4 M annually.
• Error reduction: AI‑verified item identification cuts mis‑picks from 0.7 % to 0.2 %, directly boosting customer NPS scores.

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6. Benefits for the Wider Logistics Ecosystem

1. standardized data exchange – Open‑source ROS‑2 messages enable third‑party carriers to tap into real‑time shipment status.
2. Carbon footprint reduction – Optimized robot routes cut energy consumption by 15 %,supporting EU Green Deal targets.
3. Supply‑chain resilience – AI‑driven rerouting adapts to disruptions (e.g., port strikes) within minutes, keeping inventory levels stable.

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7. Implementation Roadmap & Practical Tips

Phase	Action Items	Tips
Assessment	Map current manual workflows; define KPI baseline (order‑cycle time, pick accuracy).	Involve floor supervisors early; they provide critical edge‑case scenarios.
Pilot Deployment	Install 2 DGX H100 nodes, 30 AMRs, and 10 cobots in a midsize warehouse (e.g., Leipzig).	Use a “sandbox” SKU set to test AI models without impacting live orders.
Scale‑out & Integration	Replicate platform across 5 additional sites; integrate with ERP (SAP S/4HANA) via API gateway.	Leverage NVIDIA’s fleet management SDK for centralized firmware upgrades.
Continuous Optimization	Deploy automated A/B testing of AI routing algorithms; monitor robot health dashboards.	schedule weekly “model review” sprints with data scientists and warehouse leads.
Full Rollout	Expand to all 200+ sites; enable cross‑warehouse task sharing and demand forecasting.	Establish a governance board (Otto Logistics, NVIDIA, Reply) to oversee SLA compliance.

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8. Real‑World Example: Leipzig Fulfillment Center

• Scope: 45,000 m², 1,200 SKUs, 150 AMRs + 30 cobots.
• Results (Q4 2025):
• Order‑to‑delivery time dropped from 78 min to 52 min.
• Pick‑accuracy improved to 99.8 %.
• Energy usage per order decreased by 12 kWh.

• Key takeaway: The AI‑driven coordination layer unlocked “dynamic lane management,” allowing robots to share aisles without collisions, a capability previously possible only with static traffic rules.

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9. Future Outlook & Innovation Paths

• Edge‑AI evolution: Upcoming NVIDIA Ada‑Lovelace GPU architecture will enable on‑robot inference at sub‑millisecond latency, further reducing decision cycles.
• Digital twins: Reply plans to integrate a high‑fidelity simulation of Otto’s warehouse network, facilitating “what‑if” analyses for seasonal demand spikes.
• Autonomous transport: Expansion of the platform to control last‑mile autonomous delivery vans, creating an end‑to‑end AI‑powered logistics chain.

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